Societal implications of personalised medicine L uc a Pa ni, M.D. - - PowerPoint PPT Presentation
Workshop on personalised medicines: role of patients, consumers and healthcare professionals Societal implications of personalised medicine L uc a Pa ni, M.D. CHMP, SAWP Me mb e r, E uro pe a n Me dic ine Ag e nc y, L o ndo n UK De pt.
L uc a Pa ni, M.D.
CHMP, SAWP Me mb e r, E uro pe a n Me dic ine Ag e nc y, L
De pt. o f Psyc hia try a nd Be ha vio ura l Sc ie nc e s – Univ. o f Mia mi – USA Chie f Sc ie ntific Offic e r – E dra Pub lishing Co mpa ny – Mila n - I T
L pa ni@ mia mi.e du @ L uc a __Pa ni
London March 14th 2017
Workshop on personalised medicines: role of patients, consumers and healthcare professionals
The
expressed in this presentation are the personal views
Medicines Agency or any of their Committees. The mention of commercial products, their sources, or their use in connection with material reported herein is not to be constructed as either an actual or implied endorsement of such products by any Public Department or Health and/or Payer Services.
Disclaimer and Disclosure*
* See also the Revised Conflict of Interest Regulations approved by AIFA Board of Directors (25.03.2015) and published on the Official Journal of 15.05.2015 according to EMA policy /626261/2014 on the handling of the conflicts of interest for scientific committee members and experts. For this presentation I receive no compensation only travel reimbursement.
Biology has now become a science of information and we must change our cultural reference framework (Leroy Hood, 2003)
1925-1983
The PAM250 Matrix
Biology and Medicine are now dead Sciences, they have become Information Sciences
2011
Predictive, personalized, preventive, participatory (P4) … Leroy Hood & Stephen H. Friend
Nature Reviews Clinical Oncology 8, 184-187 (March 2011)
Personal and Human Population Numbers
◎ Earth's population = 7 billion people ◎ Exponential growth started only 200 years ago ◎ Between year 1000 and 2000 it grew 3 times faster ◎ In the last 100 years it increased from 1,5 billion to 6 ◎ Life expectancy increased by more than 35 years
Human Population Growth: Future Trend
The personal revolution: number and types of devices
Will generate 40 ZettaBytes of Healthdata by 2020
What are we talking here really?
◉ Healthcare Research ◉ Drug Discovery ◉ Insights & Risk Mgt. ◉ Virtual Assistants ◉ Imaging & Diagnostics ◉ Wearables ◉ Lifestyle Mgt & Monitoring ◉ ER & Hospital Mgt. ◉ Mental Health
Information and Internet of everything
AI Applications in Healthcare Growing Dramatically
1 PwC 5TH annual IQ survey 2 International Data Group Research
Data ≸ information ≸ knowledge
TRANSITIONING FROM DATA TO KNOWLEDGE IS A MAJOR CHALLENGE1
SYSTEMS CANNOT PROCESS LARGE VOLUMES OF DATA FROM DIFFERENT SOURCES
GROWTH OF UNSTRUCTURED, NON- CONTEXTUALIZED DATA2
Courtesy of William King, CEO of Zephyr Health (modified)
Type and size of data
Entity table Data source 1 Data source 2 Data source n Entity Attributes Entity Attributes Entity Attributes
Meta data …… …… …… …… …… …… …… …… …… …… …… ……
Innovative data analysis models could be game changer
Traditional, relational model Entity centric model
Courtesy of William King, CEO of Zephyr Health (modified)
Programmatic data transformation: Deep Learning Billions of data connections made
From internet of everything to customerization of everybody What
is one of the Giant thinking and doing?
Apple: mHealth
◉ ResearchKit, real-world research laboratory ◉ 5 app of mHealth aimed to Parkinson's disease, diabetes, cardiovascular disease, asthma and breast cancer track ◉ Recording information very useful post market studies involving large numbers of individuals over vast geographical areas ◉ Data collected every second remotely
PatientsLikeMe ◉ A network and at the same time a research platform ◉ Through the network, patients may remain in contact with other patients ◉ Sharing the experiences ◉ Opportunity to learn from the aggregate data of others and see other types of treatments
New Technologies: PatientsLikeMe
PatientsLikeMe
With nearly 500,000 members, PatientsLikeMe is a reliable source
allowed the publication of more than 80 research studies.
Societal Implications for new answers to new demands
◉ New organizational model ◉ Innovation in life sciences and biotech ◉ Possibility of avoiding recurrence of diseases ◉ Introduction and monitoring of selective drugs ◉ Preventive personalised medicine aimed at healthy individuals at risk
2014 2020
Continuous & ambient user experience
Moving toward a postApp Era
Separate apps on separate devices App Integration w. notifications providing contextual links Intelligent assistants provide basic control and automation New "app platforms" and services emerge Wearables drive context and interactions App & collaboration across devices Fluid, contextual, conversational
We are here
Deal With Complexity Make Predictions Actively Adapt Passively Learn Act Autonomously Appear to Understand Reflect a Well- Scoped Purpose
Information of everything + advanced machine learning + advanced systems
The Perfect Storm Ignited the Smart Machine Revolution
◉ The most important innovation disrupter: i.e. the ITC impact on an expanding set of end-user devices is here now ◉ This will challenge and force all of us to rethink how data-information- knowledge are being created and used ◉ Business models will evolve (fast) thanks to smart machine technologies ◉ We must augment perimeter defense and rule-based security detection with user and entity behavior analytics ◉ The difference, if any, between patients and consumers is fading away
In conclusion: Societal Implications of Personalised Medicine